forked from PoulinV/AxiCLASS
-
Notifications
You must be signed in to change notification settings - Fork 0
/
fit.log
214 lines (152 loc) · 7.13 KB
/
fit.log
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
*******************************************************************************
Mon Sep 19 11:11:13 2016
FIT: data read from "v_eff.dat" using 1:2
format = x:z
x range restricted to [1.00000 : 2000.00]
#datapoints = 3
residuals are weighted equally (unit weight)
function used for fitting: f1(x)
f1(x)=a*x+b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda a b
0 6.6082283000e+07 0.00e+00 6.17e+02 1.000000e+00 1.000000e+00
6 6.3489392193e+06 -2.23e-02 6.17e-04 3.858796e+00 2.426211e+03
After 6 iterations the fit converged.
final sum of squares of residuals : 6.34894e+06
rel. change during last iteration : -2.22535e-07
degrees of freedom (FIT_NDF) : 1
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 2519.71
variance of residuals (reduced chisquare) = WSSR/ndf : 6.34894e+06
Final set of parameters Asymptotic Standard Error
======================= ==========================
a = 3.8588 +/- 2.184 (56.61%)
b = 2426.21 +/- 1905 (78.54%)
correlation matrix of the fit parameters:
a b
a 1.000
b -0.646 1.000
*******************************************************************************
Mon Sep 19 11:11:33 2016
FIT: data read from "v_eff.dat" using 1:2
format = x:z
x range restricted to [1.00000 : 2000.00]
#datapoints = 3
residuals are weighted equally (unit weight)
function used for fitting: f1(x)
f1(x)=a*x+b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda a b
0 6.6082283000e+07 0.00e+00 6.17e+02 1.000000e+00 1.000000e+00
6 6.3489392193e+06 -2.23e-02 6.17e-04 3.858796e+00 2.426211e+03
After 6 iterations the fit converged.
final sum of squares of residuals : 6.34894e+06
rel. change during last iteration : -2.22535e-07
degrees of freedom (FIT_NDF) : 1
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 2519.71
variance of residuals (reduced chisquare) = WSSR/ndf : 6.34894e+06
Final set of parameters Asymptotic Standard Error
======================= ==========================
a = 3.8588 +/- 2.184 (56.61%)
b = 2426.21 +/- 1905 (78.54%)
correlation matrix of the fit parameters:
a b
a 1.000
b -0.646 1.000
*******************************************************************************
Mon Sep 19 11:12:01 2016
FIT: data read from "v_eff.dat" using 1:2
format = x:z
x range restricted to [1.00000 : 2000.00]
#datapoints = 3
residuals are weighted equally (unit weight)
function used for fitting: f1(x)
f1(x)=a*x+b
fitted parameters initialized with current variable values
iter chisq delta/lim lambda a b
0 6.6082283000e+07 0.00e+00 6.17e+02 1.000000e+00 1.000000e+00
6 6.3489392193e+06 -2.23e-02 6.17e-04 3.858796e+00 2.426211e+03
After 6 iterations the fit converged.
final sum of squares of residuals : 6.34894e+06
rel. change during last iteration : -2.22535e-07
degrees of freedom (FIT_NDF) : 1
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 2519.71
variance of residuals (reduced chisquare) = WSSR/ndf : 6.34894e+06
Final set of parameters Asymptotic Standard Error
======================= ==========================
a = 3.8588 +/- 2.184 (56.61%)
b = 2426.21 +/- 1905 (78.54%)
correlation matrix of the fit parameters:
a b
a 1.000
b -0.646 1.000
*******************************************************************************
Mon Sep 19 11:13:20 2016
FIT: data read from "v_eff.dat" using 1:2
format = x:z
x range restricted to [1.00000 : 2000.00]
#datapoints = 3
residuals are weighted equally (unit weight)
function used for fitting: f1(x)
f1(x)=b*x**a
fitted parameters initialized with current variable values
iter chisq delta/lim lambda a b
0 6.6106500000e+07 0.00e+00 4.55e+03 1.000000e+00 1.000000e+00
207 1.4646087671e+06 -2.25e-04 4.55e-02 3.191117e-01 7.985419e+02
After 207 iterations the fit converged.
final sum of squares of residuals : 1.46461e+06
rel. change during last iteration : -2.24657e-09
degrees of freedom (FIT_NDF) : 1
rms of residuals (FIT_STDFIT) = sqrt(WSSR/ndf) : 1210.21
variance of residuals (reduced chisquare) = WSSR/ndf : 1.46461e+06
Final set of parameters Asymptotic Standard Error
======================= ==========================
a = 0.319112 +/- 0.1108 (34.73%)
b = 798.542 +/- 605.4 (75.81%)
correlation matrix of the fit parameters:
a b
a 1.000
b -0.985 1.000
*******************************************************************************
Mon Sep 19 11:14:22 2016
FIT: data read from "v_eff.dat" using 1:2
format = x:z
x range restricted to [10.0000 : 180.000]
#datapoints = 2
residuals are weighted equally (unit weight)
function used for fitting: f1(x)
f1(x)=b*x**a
fitted parameters initialized with current variable values
iter chisq delta/lim lambda a b
0 2.3856500000e+07 0.00e+00 4.77e+02 1.000000e+00 1.000000e+00
326 1.2924697071e-26 0.00e+00 4.77e-01 6.340297e-01 1.858062e+02
After 326 iterations the fit converged.
final sum of squares of residuals : 1.29247e-26
rel. change during last iteration : 0
Exactly as many data points as there are parameters.
In this degenerate case, all errors are zero by definition.
Final set of parameters
=======================
a = 0.63403
b = 185.806
*******************************************************************************
Mon Sep 19 11:14:22 2016
FIT: data read from "v_eff.dat" using 1:2
format = x:z
x range restricted to [180.000 : 1500.00]
#datapoints = 2
residuals are weighted equally (unit weight)
function used for fitting: f2(x)
f2(x)=c*x**d
fitted parameters initialized with current variable values
iter chisq delta/lim lambda c d
0 6.5482400000e+07 0.00e+00 5.58e+03 1.000000e+00 1.000000e+00
230 0.0000000000e+00 -inf 5.58e-08 1.581389e+03 2.216723e-01
After 230 iterations the fit converged.
final sum of squares of residuals : 0
abs. change during last iteration : -3.63703e-20
Exactly as many data points as there are parameters.
In this degenerate case, all errors are zero by definition.
Final set of parameters
=======================
c = 1581.39
d = 0.221672